Course Overview of DP-750: Build Scalable Data Engineering Solutions with Azure Databricks

This course focuses on implementing data engineering solutions using Azure Databricks, a powerful Apache Spark-based analytics platform. Learners will gain expertise in building scalable data pipelines, transforming large datasets and managing distributed data processing workloads efficiently. 

The course emphasizes practical skills such as working with Delta Lake, optimizing Spark jobs, implementing structured streaming and integrating Databricks with Azure services. Participants will also learn best practices for performance tuning, data governance and production deployment. By the end of the course, learners will be equipped to design robust, high-performance data engineering solutions suitable for enterprise-scale analytics workloads. 

After completing DP-750, participants will be able to:

  • Build and manage data pipelines using Azure Databricks.
  • Use Apache Spark for distributed data processing.
  • Work with Delta Lake for reliable data storage and ACID transactions.
  • Implement batch and streaming data processing solutions.
  • Optimize Spark jobs for performance and scalability.
  • Manage Databricks clusters and workloads.
  • Integrate Databricks with Azure services like Data Factory and Synapse.
  • Implement data governance and security best practices.

Upcoming Batches

Loading Dates...

Key Features of DP-750: Build Scalable Data Engineering Solutions with Azure Databricks

  • Official Microsoft curriculum aligned with DP-750 certification 

  • Hands-on labs using Azure Databricks and Spark 

  • Deep dive into Delta Lake architecture and features 

  • Real-world use cases for batch and streaming pipelines 

  • Performance tuning and cost optimization techniques 

  • Integration with Azure ecosystem (ADF, Synapse, ADLS) 

  • Industry-relevant data engineering scenarios 

  • Instructor-led sessions with guided labs 

Who should Attend DP-750?

  • Data Engineers and Big Data Professionals
  • Azure Data Engineers working with Databricks
  • Data Analysts transitioning to engineering roles
  • Developers building data pipelines and analytics solutions
  • Application Developers building data-driven applications

Prerequisites of DP-750: Build Scalable Data Engineering Solutions with Azure Databricks

It is recommended that learners have:
  • Basic knowledge of data engineering concepts
  • Familiarity with SQL and Python/Scala
  • Understanding of cloud computing (Azure preferred)
  • Basic knowledge of big data concepts and ETL processes
  • Exposure to Spark (recommended but not mandatory)

    • Why choose CloudThat as your training partner for DP-750?

    • CloudThat provides Microsoft-certified trainers with deep expertise in Azure Databricks, Spark and real-world data engineering implementations. 
    • Hands-on labs and industry-focused scenarios ensure practical exposure to building scalable data pipelines and optimizing big data workloads. 
    • Comprehensive coverage of certification topics with exam-focused preparation materials and mock assessments aligned to DP-750 objectives. 
    • Flexible delivery options including corporate training, instructor-led online sessions and customized enterprise learning paths. 
    • Post-training support, recorded sessions and continuous learning resources help reinforce knowledge and support certification success. 
    • Proven track record in delivering high-quality Azure and data engineering training to professionals across multiple industries. 

    Learning objectives of DP-750: Build Scalable Data Engineering Solutions with Azure Databricks

    • Understand how to design scalable data engineering solutions using Azure Databricks and Apache Spark for enterprise-grade analytics workloads. 
    • Gain expertise in building and optimizing ETL pipelines using DataFrames, Spark SQL and Delta Lake storage mechanisms. 
    • Learn to implement both batch and real-time streaming solutions using structured streaming for continuous data processing scenarios. 
    • Develop skills to optimize performance and cost by tuning Spark jobs, managing clusters and implementing efficient data storage techniques. 
    • Build the ability to integrate Azure Databricks with other Azure services such as Data Factory, Synapse Analytics and ADLS Gen2. 
    • Understand best practices for data governance, security and monitoring in modern cloud-based data engineering environments. 

    Course Outline for DP-750: Build Scalable Data Engineering Solutions with Azure Databricks Download Course Outline

    • Introduction to Azure Databricks
    • Work with notebooks and clusters
    • Use Apache Spark DataFrames and SQL
    • Perform data transformations
    • Handle large-scale distributed datasets

    • Understand Delta Lake architecture
    • Implement ACID transactions
    • Perform time travel and versioning
    • Optimize storage with compaction and Z-ordering
    • Handle schema evolution and enforcement

    • Implement batch data pipelines
    • Use Structured Streaming in Spark
    • Integrate with Azure Data Factory
    • Build end-to-end ETL/ELT pipelines
    • Monitor and troubleshoot data pipelines

    Certification Details of Build Scalable Data Engineering Solutions with Azure Databricks

    • DP-750 certification validates skills in implementing data engineering solutions using Azure Databricks and Apache Spark technologies.
    • The exam evaluates abilities in data processing, Delta Lake implementation and building scalable data pipelines with streaming capabilities.
    • Candidates are expected to demonstrate knowledge of Spark optimization, cluster management and integration with Azure services.
    • Certification aligns with the Azure Data Engineer role, focusing on big data processing and modern analytics architectures.

    Click to Zoom

    Select Course date

    Loading Dates...
    Add to Wishlist

    Course ID: 28095

    Course Price at

    Loading price info...
    Enroll Now

    FAQs for DP-750: Build Scalable Data Engineering Solutions with Azure Databricks

    DP-750 focuses on implementing data engineering solutions using Azure Databricks and Apache Spark.

    It is designed for data engineers, big data professionals and developers working with large-scale data processing systems.

    Microsoft exams typically require 700 out of 1000 to pass.

    Azure Data Engineers can earn approximately ₹12–30 LPA in India and $100,000–$150,000 globally, depending on experience and expertise.

    It requires strong understanding of Spark, Databricks and data engineering concepts, making it moderately challenging.

    Azure Databricks, Apache Spark, Delta Lake, Structured Streaming, Azure Data Factory and ADLS Gen2.

    Typically, 4–6 weeks with hands-on labs and Microsoft Learn modules.

    Yes, knowledge of Python (PySpark), SQL or Scala is essential.

    4 Days

    Roles include Data Engineer, Big Data Engineer, Databricks Engineer and Analytics Engineer.

    Enquire Now